Optical navigation is an intuitive and precise way to track moving objects. The approach is intuitive because our own human stereo vision system calculates object locations and trajectories by optical triangulation. The precision of optical navigation is due to the very short wavelength of electromagnetic radiation in comparison with typical object dimensions, negligible latency in short distance measurements due to the extremely large speed of light and relative immunity to interference.
Optical navigation typically employs several cameras to determine the position or trajectory of an object in an environment by studying images of the object in the environment. Such optical capturing or tracking systems are commonly referred to as optical motion capture (MC) systems. In general, motion capture tends to be computationally expensive because of significant image pre-and post-processing requirements, as well as additional computation associated with segmentation and implementation of algorithms. One particular system taught by McSheery et al. in U.S. Pat. No. 6,324,296 discloses a distributed-processing motion capture system that employs a number of light point devices as markers, e.g., infrared LEDs, attached to the object whose motion is to be determined. The markers use unique sequences of light pulses to represent their unique identities and thus enable filtering out of information not belonging to the markers (i.e., background noise) by the imaging cameras located in the environment. Since McSheery's system permits a great deal of irrelevant information from the imaging sensors (e.g., CCDs) to be discarded before image processing, the system is less computationally expensive than more traditional motion capture systems.
Another three-dimensional position and orientation sensing system that employs markers on the object is taught by Kosaka et al. in U.S. Pat. No. 6,724,930. In this case the markers are uniquely identified based on color or a geometric characteristic of the markers in the extracted regions. The system uses an image acquisition unit or camera positioned in the environment and relies on image processing functions to remove texture and noise. Segmentation algorithms are used to extract markers from images and to determine the three-dimensional position and orientation of the object with respect to the image acquisition apparatus.
Still another way of employing markers in position and orientation detection is taught in U.S. Pat. No. 6,587,809 by Majoe. The object is tracked by providing it with markers that are activated one at a time and sensed by a number of individual sensors positioned in the environment. The position of the energized or active marker is determined by a control unit based on energy levels received by the individual sensors from that marker.
The above approaches using markers on objects and cameras in the environment to recover object position, orientation or trajectory are still too resource-intensive for low-cost and low-bandwidth applications. This is due to the large bandwidth needed to transmit image data captured by cameras, the computational cost to the host computer associated with processing image data, and the data network complexity due to the spatially complicated distribution of equipment (i.e., placement and coordination of several cameras in the environment with the central processing unit and overall system synchronization).
Under certain conditions, the large computational burden of image processing can be circumvented. Prior art teaches apparatus and methods that identify and track only a few illuminated points or markers associated with the object. Such apparatus typically employ a position sensing means such as a position sensitive detector (PSD) originally described by J. T. Wallmark, “A new semiconductor photocell using lateral photoeffect”, Proc. IRE, vol. 45, no. 4, pp. 474-483, April 1957 (see also U.S. Pat. No. 3,028,050 to J. T. Wallmark) or analogous device for sensing a position at which electromagnetic radiation associated with the object or the environment is incident on the sensor. General information about a beam position identification apparatus is contained in U.S. Pat. No. 3,209,201 to Anger. More specific teachings about an optical position sensor with a four quadrant photo-sensitive detector for measuring the X-Y position of an object based on light energy emitted from the object are found in U.S. Pat. No. 3,918,814 to Weiser.
The most successful type of position sensitive detectors (PSDs) thus far is based on a photosensitive, reverse biased p-n semiconductor junction. Salient aspects of such p-n semiconductor junction PSDs are described in U.S. Pat. No. 4,749,849 to Hoeberechts et al. and in U.S. Pat. No. 4,877,951 to Muro. Further improvements to PSD designs have been made to reduce noise, increase sensitivity and obtain a well-behaved response. Specific teachings on how to eliminate stray light is found in U.S. Pat. No. 5,869,834 to Wipenmyr, and an enhanced sensitivity PSD is discussed in U.S. Pat. No. 6,952,026 to Lindholm. The reader will find information about improved tetra-lateral PSDs in JP Pat. No. S61-108930 and an alternative circular structure PSD in JP Pat. No. H6-204555.
Several recent PSD implementations use a silicon avalanche photodiode with internal gain as described, for example, by Karplus et al. in U.S. Pat. Nos. 6,781,133 and 6,998,619. Further, U.S. Pat. No. 6,952,003 to Skurnik et al. teaches the use of a very high-speed photodetector system capable of position sensing by using a PIN photodiode array. More recently still, Gonzo et al. teach systems and methods for light spot position and color detection using discrete response position sensitive detectors (DRPSDs) in U.S. Pat. No. 7,022,966. Some devices aimed at higher resolution and less constrained PSD geometry use thin organic films to produce organic position sensitive detectors (OPSDs) as described in U.S. Pat. No. 6,995,445 to Forrest et al.
Inspired by PSD technology, U.S. Pat. No. 5,005,979 to Sontag et al. teaches how to optically determine the position of an object by providing at least one collimated beam that is issued from a particular position on the object and bearing a fixed and definite geometric relationship to the sought position. The one or more collimated beams impinge on a fluorescent foil or plate to stimulate emission, which is captured by fibers around the edge of the foil or plate and delivered to a PSD. The PSD then delivers an output signal that is proportional to the location of the “center of gravity” or centroid of the illumination. Another related PSD inspired position and orientation sensing solution using a two-dimensional approach is taught by Salcudean in U.S. Pat. No. 5,059,789.
Still another approach to three-dimensional position triangulation employing PSDs is taught by Svetkoff et al. in U.S. Pat. No. 5,812,269. Here, the PSD is employed in association with a modulated laser beam that is scanned across the object. Knowledge of object structure and its reflectance characteristics allow one to collect the reflected radiation with the aid of a PSD and extract information such as height, intensity and other data by triangulation.
A more recent use of PSD technology for object navigation is discussed by Martin Alkeryd, “Evaluation of Position Sensing Techniques for an Unmanned Aerial Vehicle”, Dissertation at the Department of Electrical Engineering, Linkoping University, 2006, chapters 4 and 8. The system studied by Alkeryd employs infrared LED markers that are attached on the object and turned on one at a time. A PSD sensor with appropriate optics is positioned on the ground in the environment to collect the light emitted from the LEDs. Since the LEDs operate in the infrared range a filter removes all light at wavelengths below 750 nm to reduce background noise caused by visible light. The teaching further suggests modulation of LED emission, including ON-OFF keying to improve signal to noise (SNR) performance of the navigation system.
The use of PSDs in optical motion capture and navigation systems brings many advantages, but is not sufficiently agile for applications involving high-precision, low-bandwidth and high capture rate navigation of small objects. In addition, the systems are ill-suited in situations where the objects are hand-held because the requirement for positioning cameras in the user's environment (e.g., working area) is constraining. For example, when navigating a hand-held object such as a mouse or a jotting implement, e.g., as described in U.S. Pat. No. 7,203,384 to Carl, the distributed nature of a motion capture system in a jotting environment even if employing PSD sensors is cumbersome.
What is needed is a high-precision, low-bandwidth and high capture rate optical navigation system for tracking objects in close-range environments. More precisely, what is required is a navigation system that is sufficiently robust to navigate even rapidly moving hand-held objects, including pointers, controllers, mice, jotting implements and other small objects in constrained environments or work-spaces.